J. Anderson, Spatially and temporally varying adaptive covariance inflation for ensemble filters, Tellus, vol.61, pp.72-83, 2009.

J. Anderson, T. J. Hoar, K. Raeder, H. Liu, N. Collins et al., The data assimilation research test bed: a community facility, Bull. Am. Meteorol. Soc, vol.90, pp.1283-1296, 2009.

M. A. Balmaseda, D. Dee, A. Vidard, A. , and D. L. , , 2007.

, A multivariate treatment of bias for sequential data assimilation: application to the tropical oceans, Q. J. R. Meteorol. Soc, vol.133, pp.167-179

T. Bayes, An essay towards solving a problem in the doctrine of chances, Philos. Trans. R. Soc, vol.53, pp.370-418, 1763.

A. F. Bennett, Inverse Modeling of the Ocean and Atmosphere, p.234, 2002.

P. Brasseur and J. Verron, The SEEK filter method for data assimilation in oceanography: a synthesis. Ocean Dyn, vol.56, pp.650-661, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00220505

M. Buehner, L. Bertino, A. Caya, P. Heimbach, and G. Smith, Sea ice data assimilation, Sea Ice Analysis and Forecasting: Towards an Increased Reliance on Automated Prediction Systems, pp.109-143, 2017.

M. Buehner and A. Shlyaeva, Scale-dependent background-error covariance localisation, Tellus A, vol.67, p.28027, 2015.

A. Carrassi, M. Bocquet, L. Bertino, and G. Evensen, Data assimilation in the geosciences: an overview of methods, issues, and perspectives, Interdiscip. Rev. Clim. Change, vol.9, p.535, 2018.

M. J. Carrier, H. E. Ngodock, S. R. Smith, I. Souopgui, and B. Bartels, Examining the potential impact of SWOT observations in an ocean analysisforecasting system, Mon. Weather Rev, vol.144, pp.3767-3782, 2016.

V. Chabot, M. Nodet, N. Papadakis, and A. Vidard, Accounting for observation errors in image data assimilation, Tellus A, vol.67, pp.4117-4119, 2015.
URL : https://hal.archives-ouvertes.fr/hal-00984508

P. Courtier, J. Thépaut, and A. Hollingsworth, A strategy for operational implementation of 4D-Var using an incremental approach, Q. J. R. Meteorol. Soc, vol.120, pp.1367-1388, 1994.

J. A. Cummings, Operational multivariate ocean data assimilation, Q. J. R. Meteorol. Soc, vol.131, pp.3583-3604, 2005.

L. D'amore, R. Arcucci, L. Carracciulo, and A. Murli, A scalable approach for variational data assimilation, J. Sci. Comput, vol.61, pp.239-257, 2014.

C. A. Edwards, A. M. Moore, I. Hoteit, and B. D. Cornuelle, Regional ocean data assimilation, Ann. Rev. Mar. Sci, vol.7, pp.6-7, 2015.

G. Evensen, The ensemble Kalman filter: theoretical formulation and practical implementation, Ocean Dyn, vol.53, pp.343-367, 2003.

M. Fisher, S. Gratton, S. Gürol, Y. Trémolet, and X. Vasseur, Low rank updates in preconditioning the saddle point systems arising from data assimilation problems, Optim. Methods Softw, vol.33, pp.45-69, 2016.

S. J. Fletcher, Mixed gaussian-lognormal four-dimensional data assimilation, Tellus A, vol.62, pp.266-287, 2010.

S. Frolov, C. H. Bishop, T. R. Holt, J. A. Cummings, and D. D. Kuhl, Facilitating strongly-coupled ocean-atmosphere data assimilation with an interface solver, Mon. Weather Rev, vol.144, pp.3-20, 2016.

P. Heimbach, I. Fukumori, C. N. Hill, R. M. Ponte, D. Stammer et al., Putting it all together: enhancing the global ocean and climate observing systems with complete self-consistent ocean state estimates, Front. Mar. Sci, vol.19, p.55, 2019.

P. L. Houtekamer and F. Zhang, Review of the ensemble Kalman filter for atmospheric data assimilation, Mon. Weather Rev, vol.144, pp.4489-4525, 2016.

K. Ide, P. Courtier, M. Ghil, and A. C. Lorenc, Unified notation for data assimilation: operational, sequential and variational, J. Meteorol. Soc. Japan, vol.75, pp.181-189, 1997.

E. Kalnay, Atmospheric Modeling, Data Assimilation and Predictability, p.341, 2003.

D. J. Lea, J. Drecourt, K. Haines, and M. J. Martin, Ocean altimeter assimilation with observational and model bias correction, Q. J. R. Meteoro. Soc, vol.134, pp.1761-1774, 2008.

J. Lellouche, O. Le-galloudec, M. Drevillon, C. Regnier, E. Greiner et al., Evaluation of global monitoring and forecasting systems at Mercator Ocean, Ocean Sci, vol.9, pp.57-81, 2013.

P. F. Lermusiaux and C. Chiu, Four-dimensional data assimilation for coupled physical-acoustical fields, Acoustic Variability, pp.417-424, 2002.

Z. Li, J. C. Mcwilliams, K. Ide, and J. D. Farrara, A multiscale variational data assimilation scheme: formulation and illustration, Mon. Weather Rev, vol.143, pp.3804-3822, 2015.

A. C. Lorenc, N. E. Bowler, A. M. Clayton, S. R. Pring, and D. Fairbairn, Comparison of hybrid-4DEnVar and hybrid-4DVar data assimilation methods for global NWP, Mon. Weather Rev, vol.143, pp.212-229, 2015.

A. C. Lorenc, J. , and M. , A comparison of hybrid variational data assimilation methods for global NWP, Q. J. R. Meteorol. Soc, vol.144, pp.2748-2760, 2018.

M. J. Martin, M. Balmaseda, L. Bertino, P. Brasseur, G. Brassington et al., Status and future of data assimilation in operational oceanography, Supp. 1), vol.8, pp.28-48, 2015.
URL : https://hal.archives-ouvertes.fr/insu-01349452

M. J. Martin, R. R. King, J. While, and A. Aguiar, Assimilating satellite sea-surface salinity data from SMOS, aquarius and SMAP into a global ocean forecasting system, Q. J. R. Meteorol. Soc. 1-22, 2019.

I. Mirouze, E. W. Blockley, D. J. Lea, M. J. Martin, and M. J. Bell, A multiple length scale correlation operator for ocean data assimilation, Tellus A, vol.68, pp.1-13, 2016.

A. M. Moore, H. G. Arango, E. Di-lorenzo, B. D. Cornuelle, A. J. Miller et al., A comprehensive ocean prediction and analysis system based on the tangent linear and adjoint of a regional ocean model, Ocean Model, vol.7, pp.227-258, 2004.

L. Nerger and W. Hiller, software for ensemble-based data assimilation systems -implementation strategies and scalability, Comput. Geosci, vol.55, pp.110-118, 2013.

P. Oddo, A. Storto, S. Dobricic, A. Russo, C. Lewis et al., A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models, Ocean Sci, vol.12, pp.1137-1153, 2016.

P. R. Oke, J. S. Allen, R. N. Miller, G. D. Egbert, and P. M. Kosro, Assimilation of surface velocity data into a primitive equation coastal ocean model, J. Geophys. Res, vol.107, p.3122, 2002.

P. R. Oke and P. Sakov, Representation error of oceanic observations for data assimilation, J. Atmospher. Ocean. Technol, vol.25, pp.1004-1017, 2008.

P. R. Oke, P. Sakov, and S. P. Corney, Impacts of localisation in the EnKF and EnOI: experiments with a small model, Ocean Dyn, vol.57, pp.32-45, 2007.

S. G. Penny, D. W. Behringer, J. A. Carton, and E. Kalnay, A hybrid global ocean data assimilation system at, NCEP. Mon. Weather Rev, vol.143, pp.4660-4677, 2015.

K. Raghukumar, C. A. Edwards, N. L. Goebel, G. Broquet, M. Veneziani et al., Impact of assimilating physical oceanographic data on modeled ecosystem dynamics in the California Current System, Prog. Oceanogr, vol.138, pp.546-558, 2015.

P. Sakov, EnKF-C user guide, 2014.

P. Sakov and P. A. Sandery, Comparison of EnOI and EnKF regional ocean reanalysis systems, Ocean Model, vol.89, pp.45-60, 2015.

E. Simon and L. Bertino, Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem model of the North Atlantic with the EnKF: a twin experiment. Ocean Model, vol.4, pp.495-510, 2009.

A. Storto, P. Oddo, A. Cipollone, I. Mirouze, and B. Lemieux, Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation. Ocean Model, vol.128, pp.67-86, 2018.

A. Storto, C. Yang, and S. Masina, Constraining the global ocean heat content through assimilation of CERES-derived TOA energy imbalance estimates, Geophys. Res. Lett, vol.44, pp.10520-10529, 2017.

O. Talagrand, 4D-VAR: four-dimensional variational assimilation, Advanced Data Assimilation for Geosciences, p.584, 2014.

T. Toyoda, Y. Fujii, T. Kuragano, J. P. Matthews, H. Abe et al., Improvements to a global ocean data assimilation system through the incorporation of aquarius surface salinity data, Q. J. R Meteorol. Soc, vol.141, pp.2750-2759, 2015.

M. Valdivieso, K. Haines, M. Balmaseda, Y. S. Chang, M. Drevillon et al., An assessment of air-sea heat fluxes from ocean and coupled reanalyses, Clim. Dyn, vol.49, pp.983-1008, 2015.

,. Van-leeuwen, Y. Cheng, and S. Reich, Nonlinear Data Assimilation, p.117, 2015.

J. Waters, M. J. Bell, M. J. Martin, and D. J. Lea, Reducing ocean model imbalances in the equatorial region caused by data assimilation, Q. J. R. Meteorol. Soc, vol.143, pp.195-208, 2017.

A. T. Weaver and P. Courtier, Correlation modelling on the sphere using a generalized diffusion equation, Q. J. R. Meteorol. Soc, vol.127, pp.1815-1846, 2001.

A. T. Weaver, C. Deltel, R. Machu, S. Ricci, and N. Daget, A multivariate balance operator for variational ocean data assimilation, Q. J. R. Meteorol. Soc, vol.131, pp.3605-3625, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00125249

C. K. Wikle and L. M. Berliner, A Bayesian tutorial for data assimilation, Physica D, vol.230, pp.1-16, 2007.